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Client/server based statistical computing

Author

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  • Kleinow, Torsten
  • Lehmann, Heiko

Abstract

We propose a client server architecture for statistical computing. The main feature of our approach is the possibility to connect various client programs via a TCP/IP connection to a powerful statistical engine. This offers the opportunity to include the statistical engine into a number of software packages and to empower the user of these packages to access a modern statistical programming environment. It also allows for the development of specialized client programs for particular tasks. TCP/IP permits a client/server connection with the client and server running on different hosts (remote host) as well as running both applications on the same computer (local host). To have a large flexibility we suggest adding a middleware program managing the communication between Server and Client. This avoids the need to implement TCP/IP communication methods on the server side. The paper provides an overview of the desired environment and illustrates the general structure by the implementation of the XploRe Quantlet Client and XploRe Quantlet Server.

Suggested Citation

  • Kleinow, Torsten & Lehmann, Heiko, 2002. "Client/server based statistical computing," SFB 373 Discussion Papers 2002,49, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:200249
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    File URL: https://www.econstor.eu/bitstream/10419/65367/1/726722812.pdf
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    References listed on IDEAS

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    1. Klinke, Sigbert & Witzel, Rodrigo, 2002. "MD*Book online: A tool for creating interactive documents," SFB 373 Discussion Papers 2002,21, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
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    Cited by:

    1. Klinke, Sigbert & Kuhlee, Dina & Theel, Christian & Wagner, Cornelia & Westermeier, Christian, 2009. "MM-Stat - MultiMedia-Statistik: Statistische Datenanalyse - webbasiert, interaktiv und multimedial," SFB 649 Discussion Papers 2009-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

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